Abstract

Magnetic Abrasive Finishing (MAF) is an advanced finishing process in which the cutting force is controlled by magnetic field and it provides a high level of surface finish and close tolerances for wide range of industrial application. In this study the parameter that affects surface roughness in MAF process on a brass shaft of CuZn37 have been examined experimentally. These parameters are: intensity of the magnetic field, work-piece velocity and finishing time. It has been shown that the intensity of magnetic field has the most effect on finishing process, a higher intensity in magnetic field, results in a higher change in surface roughness, increasing finishing time results in decreased surface roughness and a lower work-piece velocity leads to a lower surface roughness. Finally Artificial Neural Network (ANN) prediction of surface roughness are carried out and compared with experiment. It was found that the coefficient of multiple determinations (R2-value) between the experimental and ANN predicted data is equal to about 0.999, therefore, indicating the possibility of ANN as a strong tool in simulating and prediction of surface roughness in MAF process.

Keywords:

Artificial neural network, brass finishing, magnetic abrasive, surface roughness,

References

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.